Enabling data availability for AI & decisions, across the enterprise


Traditional data technology creates friction for insights

Data silos

Enterprise data is often siloed and difficult to access, with access requiring multiple tools, data duplication, and specialized knowledge.

It takes too long to go from data to insight

Business users wait for data teams to prepare insights that are often updated by the time they're ready.

Current tools aggregate, not curate

Most tools available are focused on "dumb data aggregation", without curation and context.

Unify access to data for decision-making & AI/ML
while maintaining data governance

App Orchid's intelligence fabric is based on knowledge graphs to enable a wide range of data science,
machine learning (ML) and artificial intelligence (AI) applications.

Enable an Enterprise data fabric with intelligence

The App Orchid intelligence fabric unlocks the data locked in different systems and applications and assigns meaning and context in a semantic data fabric.

Infuse Enterprise data, knowledge hidden in documents and more with behavior to effortlessly deliver unified access to governed, meaningful data to your data consumers – including AI/data science teams, business users and C-suite.


AI built into the graph enables rapid and consistent outcomes

Machine Learning, Optimization, and Statistical Models are embedded in the App Orchid graph enabling predictions and optimizing business decisions.


Onboard your data in seconds

Automated Ontology Discovery speeds up deployment by automating the building of the Enterprise Knowledge graph, and data enrichment process.

Turn siloed data into flexible, scalable knowledge graphs that unify data by meaning, not location, and reveal new relationships.


Low impact, high performance

Only store key data in the graph, while the bulk of your data is still stored in systems of record. Access data without replication to reduce costs while maintaining existing data governance controls.


Integrate many different types of Enterprise data sources with

Structured enterprise data
Unstructured documents
Geospatial data
External Content Sources

External content

Public Data

+ Custom

How it works

Step 1:

Build a baseline ontology based on a core business question.

Step 2:

Align data to the ontology automatically using the ontology discovery module

Step 3:

Explore data in the knowledge graph using natural language to ask questions

Step 4:

Get more answers by repeating earlier steps to add more domains, data, users, and use cases.

Semantic Data Engine Benefits

Enable holistic, data-centric decision-making

by closing gaps in understanding of customers, products, and processes. 

Improve data accessibility

for business users, as it unifies and governs data environments. 

Enable integration of new data sources

and the discovery of new opportunities to improve business performance.

Eliminate Data Silos

and bottlenecks in decision-making by providing a unified view of the data. 

See how we transformed a Utility, running 10+ business critical apps on an Enterprise Knowledge Graph